Build vs Buy Economics

The financial case for building your own AI versus buying from a vendor is rarely as clear-cut as either side would like. Building gives you customisation and control but requires significant upfront investment, ongoing maintenance costs, and specialised talent that's expensive and hard to find. Buying gets you to market faster and shifts maintenance burden to the vendor but comes with licensing fees, potential lock-in, and the risk that the product doesn't quite fit your needs. The economics depend heavily on your specific situation: how core the AI capability is to your competitive advantage, how much customisation you genuinely need, whether you can attract and retain the right talent, and your time-to-value requirements. Many organisations underestimate the total cost of building - not just the initial development but years of maintenance, upgrades, and operational support. Equally, the costs of buying can escalate as you scale, particularly with usage-based pricing models. A honest assessment considers the full lifecycle costs of both options, factors in the opportunity cost of engineering time, and acknowledges that "build" and "buy" aren't binary - most organisations end up with a mix, building where differentiation matters and buying commodity capabilities.